



'''simple docstring'''






from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable


lowerCAmelCase:   List[Any]					=		{
    'configuration_gpt_neox_japanese': ['GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXJapaneseConfig'],
    'tokenization_gpt_neox_japanese': ['GPTNeoXJapaneseTokenizer'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:   Union[str, Any]					=		[
         'GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST',
         'GPTNeoXJapaneseForCausalLM',
         'GPTNeoXJapaneseLayer',
         'GPTNeoXJapaneseModel',
         'GPTNeoXJapanesePreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
     from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gpt_neox_japanese import (
              GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTNeoXJapaneseForCausalLM,
              GPTNeoXJapaneseLayer,
              GPTNeoXJapaneseModel,
              GPTNeoXJapanesePreTrainedModel,
          )


else:
     import sys

     lowerCAmelCase:   Optional[int]					=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




'''simple docstring'''






import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase:   Tuple					=		logging.get_logger(__name__)

lowerCAmelCase:   Dict					=		'▁'

lowerCAmelCase:   Dict					=		{
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
}

lowerCAmelCase:   int					=		{
    'vocab_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json'
        ),
    },
    'spm_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model'
        )
    },
}

lowerCAmelCase:   Any					=		{
    'facebook/s2t-small-librispeech-asr': 1_0_2_4,
}

lowerCAmelCase:   Optional[int]					=		['pt', 'fr', 'ru', 'nl', 'ro', 'it', 'es', 'de']

lowerCAmelCase:   List[Any]					=		{'mustc': MUSTC_LANGS}

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       VOCAB_FILES_NAMES
    lowercase__					=       PRETRAINED_VOCAB_FILES_MAP
    lowercase__					=       MAX_MODEL_INPUT_SIZES
    lowercase__					=       ["""input_ids""", """attention_mask"""]

    lowercase__					=       []







    def __init__( self					:    int		,     __snake_case					:    int		,     __snake_case					:    Optional[Any]		,     __snake_case					:    Optional[Any]="<s>"		,     __snake_case					:    Optional[int]="</s>"		,     __snake_case					:    Union[str, Any]="<pad>"		,     __snake_case					:    str="<unk>"		,     __snake_case					:    Dict=False		,     __snake_case					:    int=False		,     __snake_case					:    str=None		,     __snake_case					:    Optional[int]=None		,     __snake_case					:    Optional[Dict[str, Any]] = None		,     **__snake_case					:    Union[str, Any]		,     ):
      a		:   Union[str, Any]	  =	{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=__snake_case		,     eos_token=__snake_case		,     unk_token=__snake_case		,     pad_token=__snake_case		,     do_upper_case=__snake_case		,     do_lower_case=__snake_case		,     tgt_lang=__snake_case		,     lang_codes=__snake_case		,     sp_model_kwargs=self.sp_model_kwargs		,     **__snake_case		,     )
      a		:   Tuple	  =	do_upper_case
      a		:   Optional[Any]	  =	do_lower_case

      a		:   List[str]	  =	load_json(__snake_case      )
      a		:   Dict	  =	{v: k for k, v in self.encoder.items()}
      a		:   int	  =	spm_file
      a		:   Tuple	  =	load_spm(__snake_case		,     self.sp_model_kwargs      )

      if lang_codes is not None:
        a		:   Any	  =	lang_codes
        a		:   str	  =	LANGUAGES[lang_codes]
        a		:   Tuple	  =	[F"""<lang:{lang}>""" for lang in self.langs]
        a		:   str	  =	{lang: self.sp_model.PieceToId(F"""<lang:{lang}>"""      ) for lang in self.langs}

        a		:   Optional[Any]	  =	self.lang_tokens
        a		:   Union[str, Any]	  =	tgt_lang if tgt_lang is not None else self.langs[0]

        self.set_tgt_lang_special_tokens(self._tgt_lang      )
      else:
        a		:   List[str]	  =	{}







    @property
    def      lowercase_			( self					:    Optional[Any]      ):
      return len(self.encoder      )







    @property
    def      lowercase_			( self					:    int      ):
      return self._tgt_lang







    @tgt_lang.setter
    def      lowercase_			( self					:    int		,     __snake_case					:    Optional[int]      ):
      a		:   Union[str, Any]	  =	new_tgt_lang
      self.set_tgt_lang_special_tokens(__snake_case      )







    def      lowercase_			( self					:    str		,     __snake_case					:    str      ):
      a		:   int	  =	self.lang_code_to_id[tgt_lang]
      a		:   int	  =	[lang_code_id]







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    str      ):
      return self.sp_model.encode(__snake_case		,     out_type=__snake_case      )







    def      lowercase_			( self					:    List[str]		,     __snake_case					:    List[Any]      ):
      return self.encoder.get(__snake_case		,     self.encoder[self.unk_token]      )







    def      lowercase_			( self					:    List[Any]		,     __snake_case					:    int      ):
      return self.decoder.get(__snake_case		,     self.unk_token      )







    def      lowercase_			( self					:    Union[str, Any]		,     __snake_case					:    List[str]      ):
      a		:   List[Any]	  =	[]
      a		:   List[Any]	  =	''
      for token in tokens:
        # make sure that special tokens are not decoded using sentencepiece model
        if token in self.all_special_tokens:
          a		:   Union[str, Any]	  =	self.sp_model.decode(__snake_case      )
          out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
          a		:   Optional[int]	  =	[]
        else:
          current_sub_tokens.append(__snake_case      )
      a		:   Tuple	  =	self.sp_model.decode(__snake_case      )
      out_string += decoded.upper() if self.do_upper_case else decoded
      return out_string.strip()







    def      lowercase_			( self					:    int		,     __snake_case					:    List[Any]		,     __snake_case					:    List[str]=None      ):
      if token_ids_a is None:
        return self.prefix_tokens + token_ids_a + [self.eos_token_id]
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return self.prefix_tokens + token_ids_a + token_ids_a + [self.eos_token_id]







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    List[int]		,     __snake_case					:    Optional[List[int]] = None		,     __snake_case					:    bool = False      ):

      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=__snake_case		,     token_ids_a=__snake_case		,     already_has_special_tokens=__snake_case      )

      a		:   Optional[int]	  =	[1] * len(self.prefix_tokens      )
      a		:   Any	  =	[1]
      if token_ids_a is None:
        return prefix_ones + ([0] * len(__snake_case      )) + suffix_ones
      return prefix_ones + ([0] * len(__snake_case      )) + ([0] * len(__snake_case      )) + suffix_ones







    def      lowercase_			( self					:    Union[str, Any]      ):
      a		:   Union[str, Any]	  =	self.encoder.copy()
      vocab.update(self.added_tokens_encoder      )
      return vocab







    def __getstate__( self					:    Any      ):
      a		:   List[str]	  =	self.__dict__.copy()
      a		:   Union[str, Any]	  =	None
      return state







    def __setstate__( self					:    str		,     __snake_case					:    Dict      ):
      a		:   Dict	  =	d

      # for backward compatibility
      if not hasattr(self		,     'sp_model_kwargs'      ):
        a		:   int	  =	{}

      a		:   Any	  =	load_spm(self.spm_file		,     self.sp_model_kwargs      )







    def      lowercase_			( self					:    str		,     __snake_case					:    str		,     __snake_case					:    Optional[str] = None      ):
      a		:   Union[str, Any]	  =	Path(__snake_case      )
      assert save_dir.is_dir(), F"""{save_directory} should be a directory"""
      a		:   Any	  =	save_dir / (
          (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
      )
      a		:   List[Any]	  =	save_dir / (
          (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
      )

      save_json(self.encoder		,     __snake_case      )

      if os.path.abspath(self.spm_file      ) != os.path.abspath(__snake_case      ) and os.path.isfile(self.spm_file      ):
        copyfile(self.spm_file		,     __snake_case      )
      elif not os.path.isfile(self.spm_file      ):
        with open(__snake_case		,     'wb'      ) as fi:
          a		:   Tuple	  =	self.sp_model.serialized_model_proto()
          fi.write(__snake_case      )

      return (str(__snake_case      ), str(__snake_case      ))
def  lowerCamelCase__			(		_A					,     _A							):
  a		:   List[Any]	  =	sentencepiece.SentencePieceProcessor(**_A							)
  spm.Load(str(_A							)							)
  return spm
def  lowerCamelCase__			(		_A							):
  with open(_A					,     'r'							) as f:
    return json.load(_A							)

def  lowerCamelCase__			(		_A					,     _A							):
  with open(_A					,     'w'							) as f:
    json.dump(_A					,     _A					,     indent=2							)